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PUBLICATIONS

Evaluating Uncertainty of Nonlinear Microwave Calibration Models with Regression Residuals

Published

Author(s)

Dylan F. Williams, Benjamin F. Jamroz, Jake D. Rezac

Abstract

We use synthetic data to investigate the performance of a recently developed algorithm that uses regression residuals to evaluate the uncertainty of nonlinear multivariate microwave calibration models. We verify the results with measurements.
Citation
IEEE Transactions on Microwave Theory and Techniques
Pub Type
Journals

Download Paper

https://doi.org/10.1109/TMTT.2020.3005170
Local Download

Keywords

Calibration, measurement, microwave, uncertainty, vector network analyzer
Electronics and Advanced communications

Citation

Williams, D. , Jamroz, B. and Rezac, J. (2020), Evaluating Uncertainty of Nonlinear Microwave Calibration Models with Regression Residuals, IEEE Transactions on Microwave Theory and Techniques, [online], https://doi.org/10.1109/TMTT.2020.3005170 (Accessed October 9, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created September 8, 2020, Updated October 9, 2020
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